• Journal of Sensor Science and Technology
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• v.29 no.6
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• pp.412-419
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• 2020

In this study, a PID control method for sweeping automatic linearization of a wavelength swept laser is proposed. First, the closedloop transfer function embodying the PID control is derived. Through the simulation of the function, K_p = 0.022, K_i = 0.008, K_d = 0.002 were obtained as the best PID coefficients for fast linear sweeping. The performance test using the PID coefficients showed that linear sweeping was held up well with a 98.7% decrement in nonlinearity after the 10th feedback, and 45 nm sweeping range, 1 kHz sweeping frequency, and 8.8 mW average optical power were obtained. The equipment consists of a fiber Bragg grating array, an optical-electronic conversion circuit, and a LabVIEW FPGA program. Every 5s, automatic feedback and PID control generate a new compensated waveform and produce a better linear sweeping than before. Compared with nonlinear sweeping, linear sweeping can reduce the cumbersome and time-consuming recalibration processes and produce more accurate measurement results.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.139-147
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• 1996

PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.57-64
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• 1994

This paper proposes a fuzzy tuning PID controller for straight line type inverted pendulum. The conventional PID controller which is used widely in industrial field has fatal drawback on determining control gains for practical system. The proposed controller tunes the gains automatically based on fuzzy urle derived from the experience of expert operator. The results of simulation and experiment show the efficiency of the proposed control method comparing with conventional PID control method in terms of rising time, overshoot, and overall errors.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.145-148
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• 2003

In this paper an nonlinear neuro PID controller is constructed by the control system of general PID controller using a Self-Recurrent Neural Network. And the games of the PID controller in the proposed control system are automatically adjusted by back-propagation algorithm of the neural network. Applying to the position control system, it's performance is verified through the results of computer simulation.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.49-54
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• 2003

In this paper, we propose a controller with the self-organizing neural network compensator for compensating PID controller's response. PID controller has simple design method but needs a lot of trials and errors to determine coefficients. A neural network control method does not have optimal structure as the parameters are pre-specified by designers. In this paper, to solve this problem, we use a self-organizing neural network which has Back Propagation Network algorithm using a Gaussian Potential Function as an activation function of hidden layer nodes for compensating PID controller's output. Self-Organizing Neural Network's learning is proceeded by Gaussian Function's Mean, Variance and number which are automatically adjusted. As the results of simulation through the second order plant, we confirmed that the proposed controller get a good response compare with a PID controller. And we implemented the of controller performance hydraulic servo motor system using the DSP processor. Then we observed an experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.505-505
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• 2000

Controlling the process by PID controller is widely used in industry by applying Ziegler-Nichols method in analyzing parameter of the controller. However, in fact. it is still necessary to tune parameter in order to obtain the best process response. This paper presents a Self-Tuning PID controller utilizes the personal computer to synthesize and analyze controller parameter as well as tune for appropriate parameter by using Dahlin method and Extrapolation. Experimental results using a Self-Tuning PID controller to control water level and temperature, it is found that the controller being developed is able to control the process very effectively and provides a good response similar to the controller used in the industry.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1202-1209
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• 2018

This paper is concerned with the problem of setting controller's parameters when applying the intelligent PID (i-PID), which has recently been proposed and had many successful results, to the two-degree-of-freedom (2DoF) PID controller structure. Generally, the parameter settings of conventional PID controllers are known to be quite difficult and be dependent on the characteristics of the plants. In addition, it is less known how the two 2DoF parameters are set up for the improvement of transient characteristics. Here, we are going to present one of the criteria for parameter setting in the case of using a 2DoF i-PID, by evaluating the error signals to the set-point and disturbance. That is, we first, obtain parameters of i-PID by optimizing the disturbance responses, and then determine two parameters of 2DoF component through optimizing set-point response. The standard values of all parameters are calculated for the 7 types of test batches and rounded up as a table.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.61-66
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• 2007

PID control is windely used to control stable processes, however, its application to integrating processes is less common. In this paper we proposed a simple PID controller tuning method for integrating processes with time delay to meet a stable specification. With the proposed PID tuning method, we can obtain stable integrating processes using PD controller in inner feedback loop and a loop transfer function with desired stable specification. This guarantees bout robustness and performance. Simulation examples are given to show the good performance of the proposed tuning method to other methods.

• Journal of Power System Engineering
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• v.15 no.2
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• pp.69-77
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• 2011

In this paper, an optimal PID sliding mode controller is proposed for the position control of electro-hydrostatic actuator(ERA) systems with system uncertainties and saturation in the motor. An ERA prototype is developed and system modeling and parameter identification are executed. Then, optimal PID and optimal anti-windup PID controller are designed based on identified system model by using optimization toolbox in MA TLAB/Simulink and the performance of the two control systems are compared by experiment. It was found that the optimal anti-windup PID control system has better performance than the optimal anti-windup PID control system.

• Journal of Aerospace System Engineering
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• v.4 no.4
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• pp.18-27
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• 2010

Quadrotor is an aircraft which is possible in Vertical Take-off and Landing(VTOL). This aircraft can not only be created as an Unmanned Aerial Vehicle(UAV), but also can be easily used in various fields because of its simplicity of construction. This study is mainly conducted with two main purposes. The first goal is designing the quadrotor focusing on the lightweight and protecting the airframe. The second purpose is stabilizing the quadrotor's attitude by using the PID controller. MATLAB simulation is performed for obtaining PID gain based on equations of motion. We used the compensation filter technique for the calibration of sensor data. PID gain has been drawn out based on the MATLAB simulation. The efficiency of the attitude control is improved by calibration of sensor data.